EEG Analysis of Working Memory between Sober State and Intoxicated State

Abstract

More and more people are exposed to drinking and in addicted. In recent years, Electroencephalography (EEG) technology has been used to diagnose the effects of alcohol on brain structure and functions. Since the brain contains a variety of different functions, it is difficult to explore the effects of alcohol on a certain cognitive function by single tasks to induce EEG signals. Additionally, alcohol has an effect on the performance of the working memory (WM) which is particularly susceptible to external stimulus and recovering in the short-term. This study investigates the differences of the EEG signals on the WM-load before and after alcohol intake by using the working memory tasks. Ten participants take part in the N-back experiments with taking alcohol. After preprocessing the EEG signals, seven different features are selected to classify the different WM-load levels, and these features are also used to distinguish the states whether in drinking or not. At last, the support vector machine (SVM) is applied for the classification and the accuracies for some subjects can achieve 100% in the time domain. This work not only provides a new way to explore the effects of alcohol on the specific functions of the brain but also indicates that mild alcohol consumption could alter the perception of the brain on working memory load and reduce the WM-load level.